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20242026
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cs.CL2026

BioPulse-QA: A Dynamic Biomedical Question-Answering Benchmark for Evaluating Factuality, Robustness, and Bias in Large Language Models

Kriti Bhattarai, Vipina K. Keloth, Donald Wright +3

Objective: Large language models (LLMs) are increasingly applied in biomedical settings, and existing benchmark datasets have played an important role in supporting model developme…

cs.CL2026

EHRNavigator: A Multi-Agent System for Patient-Level Clinical Question Answering over Heterogeneous Electronic Health Records

Lingfei Qian, Mauro Giuffre, Yan Wang +11

Clinical decision-making increasingly relies on timely and context-aware access to patient information within Electronic Health Records (EHRs), yet most existing natural language q…

cs.CL2025

Toward Automated Cognitive Assessment in Parkinson's Disease Using Pretrained Language Models

Varada Khanna, Nilay Bhatt, Ikgyu Shin +4

Understanding how individuals with Parkinson's disease (PD) describe cognitive experiences in their daily lives can offer valuable insights into disease-related cognitive and emoti…

cs.CL2025

Benchmarking large language models for biomedical natural language processing applications and recommendations

Qingyu Chen, Yan Hu, Xueqing Peng +18

The rapid growth of biomedical literature poses challenges for manual knowledge curation and synthesis. Biomedical Natural Language Processing (BioNLP) automates the process. While…

cs.CL2025

Information Extraction from Clinical Notes: Are We Ready to Switch to Large Language Models?

Yan Hu, Xu Zuo, Yujia Zhou +9

Backgrounds: Information extraction (IE) is critical in clinical natural language processing (NLP). While large language models (LLMs) excel on generative tasks, their performance…

cs.CL2024

Me LLaMA: Foundation Large Language Models for Medical Applications

Qianqian Xie, Qingyu Chen, Aokun Chen +15

Recent advancements in large language models (LLMs) like ChatGPT and LLaMA show promise in medical applications, yet challenges remain in medical language comprehension. This study…